Just as I was teaching my first year students, spring atmospheric conditions can vary dramatically over the years and especially the moment of spring thaw varies a lot in continental Poland. Some years, only by April did temperatures rose above 0 degrees and flooding started, while other years, already in January the spring-thaw flood was well underway. This year was one of the latter, so we expected water levels to have receded by April to facilitate collecting some of the sediment-trapping mats we placed on the floodplain.

But I did not start this blog for no reason with my lesson to the first year students. By the end of March, a rain period initiated a second flood period and our grass mats and Phillips samplers were submerged again. We still went to the field, because particularly the transport of sediment in the river is very interesting during such a second rain-flood peak (compared to the first snowmelt-flood). For the grass mats on the floodplain, all we did was checking if they were not trampled by elk or turned upside-down by a tractor. This gave me ample time to take some pictures. In May, we will return to finish the job!

Using millions of images and machine learning, Orbital Insight will be able to estimate global oil surpluses, weeks ahead of existing techniques, by analysing the shadows on the floating lids of oil tanks.

I read an article recently about a project called Orbital Insight. This is an idea to use recent, high resolution satellite imagery in addition with image recognition software to provide an up-to-date, global picture of everything from crop yields to oil surpluses (indicated by the shape of shadows on floating lids of oil tanks). The idea is that with the vast amounts of data now available and computing power to process it we can gain unprecedented insights about our planet. The founder of orbital insight, James Crawford, likened these advances to a “macroscope” that could impact our understanding of the world to a similar degree that the microscope did.

Much of these kinds of data are now openly available via the Google Earth Engine. This is a web-hosted GIS platform that exploits Googles’ ability to access pretty much any online datasets from Landsat imagery to sea surface temperature from NOAA. A high profile use of the tool recently was a paper in Science that showed global trends in deforestation and afforestation. I’d encourage anyone with an interest in these kind of datasets to go have a play. There are some nice examples of the kinds of analysis you can do on the homepage. Within the data catalog you can simply search for whichever dataset you wish to view. I searched for light and could view the DMSP-OLS Nighttime Lights Time Series. Interesting to see the big change in regions such as the Yangtze River delta! In order to have full access to all the functionality you need to apply for access as a developer. Have fun!

When I am talking about a massive large-scale event which feels very small. Which covers loads of topics, yet is very specific. An event which is attended by juniors and seniors alike; PhD’s, postdocs, full profs and even consultants. Which is focused on one main topic. A topic that is booming business nowadays! YES! I’m talking about the general assembly of the European Geosciences Union! But we just call it EGU…

Once a year, the whole Copernicus Institute gathers together at a remote place to discuss overarching topics, to have workshops together and to meet in an informal way. This year, 'De Lage Vuursche’ was our inspiring location in the woods. As the institute is growing fast, I think it is very good to catch up during those two days.